AbstractIntroduction: In external beam radiotherapy, patient verification and tumor localization must be taken into account to fill the gap between personalized treatment planning and uncertainties at pre-treatment step during therapeutic beam irradiation. In this study in order to addresses the limitation of conventional patient, a new method based on image registration technique and an intelligent correlation model is proposed to calculate inter and intra-fraction motion errors. Material and method: The configuration of the marker-less method is built by using 4DCT datasets. Firstly, the MeVisLab software package is used to extract 3D patient surface and determine the location of tumor volume. Then, the 3D surface of the patient which is included the breathing phases is imported into the MATLAB software package in order to define several control points on the thorax region as virtual external markers. At pre-treatment step, by synchronizing information of external markers and tumor location, new datasets of external breathing signals are assembled. Finally based on correlation between breathing signals/patient position and breathing signals/tumor coordinate, an adaptive neuro fuzzy inference system is proposed to both verification and alignment inter and intra-fraction motion errors in radiotherapy, if needed. Also, this technique is validated through simulation activities by using the 4DCT data acquired from four real patients.Results: Final results represent that our hybrid configuration method is capable to align patient setup with less uncertainties regarding with other available methods. The average 3D RMSE for 10 irradiation fraction of one typical patient is 0.4432 mm and for all patients it reduced from 5.26 mm to 1.5 mm.Conclusion: In this study, a marker-less method based on the image registration technique in combination with a correlation model is proposed to addresses the limitation of available methods which are: operator attentions, using passive markers, rigid-only constraint for patient setup.